---
language:
- ga
- en
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- ymoslem/IWSLT2023-GA-EN
- ymoslem/FLEURS-GA-EN
- ymoslem/BitesizeIrish-GA-EN
- ymoslem/SpokenWords-GA-EN-MTed
metrics:
- bleu
- wer
model-index:
- name: Whisper Medium GA-EN Speech Translation Raw
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: IWSLT-2023, FLEURS, BiteSize, and SpokenWords
      type: ymoslem/IWSLT2023-GA-EN
    metrics:
    - name: Bleu
      type: bleu
      value: 30.23
    - name: Wer
      type: wer
      value: 65.37595677622693
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Medium GA-EN Speech Translation Raw

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the IWSLT-2023, FLEURS, BiteSize, and SpokenWords dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4321
- Bleu: 30.23
- Chrf: 48.18
- Wer: 65.3760

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bleu  | Chrf  | Wer      |
|:-------------:|:------:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 2.6013        | 0.0539 | 100  | 2.2401          | 3.18  | 17.57 | 139.4417 |
| 2.5749        | 0.1079 | 200  | 3.0398          | 0.0   | 3.87  | 100.4052 |
| 2.3449        | 0.1618 | 300  | 2.0560          | 7.53  | 24.09 | 121.0266 |
| 2.0392        | 0.2157 | 400  | 1.9721          | 10.7  | 29.63 | 109.7253 |
| 1.9155        | 0.2697 | 500  | 1.9402          | 16.73 | 31.59 | 81.9901  |
| 1.9148        | 0.3236 | 600  | 1.7868          | 11.12 | 32.9  | 117.1544 |
| 1.698         | 0.3776 | 700  | 1.7244          | 20.14 | 36.31 | 83.8811  |
| 1.7283        | 0.4315 | 800  | 1.6586          | 16.74 | 34.0  | 94.5070  |
| 1.5213        | 0.4854 | 900  | 1.6387          | 19.49 | 38.29 | 84.2413  |
| 1.3123        | 0.5394 | 1000 | 1.6292          | 22.27 | 41.45 | 80.2792  |
| 1.1584        | 0.5933 | 1100 | 1.5900          | 25.48 | 42.03 | 74.2008  |
| 1.1734        | 0.6472 | 1200 | 1.5495          | 17.77 | 40.1  | 106.9338 |
| 1.2271        | 0.7012 | 1300 | 1.4978          | 21.7  | 43.63 | 84.2413  |
| 1.0872        | 0.7551 | 1400 | 1.4690          | 25.34 | 43.98 | 74.2909  |
| 0.9331        | 0.8091 | 1500 | 1.4688          | 20.09 | 43.14 | 90.5448  |
| 0.7861        | 0.8630 | 1600 | 1.4284          | 26.49 | 46.76 | 76.4971  |
| 0.8392        | 0.9169 | 1700 | 1.3909          | 27.22 | 46.91 | 73.3904  |
| 0.7236        | 0.9709 | 1800 | 1.4349          | 26.98 | 46.01 | 74.2008  |
| 0.2741        | 1.0248 | 1900 | 1.4279          | 28.92 | 47.63 | 68.3476  |
| 0.2782        | 1.0787 | 2000 | 1.4321          | 30.23 | 48.18 | 65.3760  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1